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Lexical Translation with Application to Image Search on the Web Oren Etzioni, Kobi Reiter, Stephen Soderland, and Marcus Sammer
 

Summary: Lexical Translation with Application to Image Search on the Web
Oren Etzioni, Kobi Reiter, Stephen Soderland, and Marcus Sammer
Turing Center
Dept. of Computer Science and Engineering
University of Washington, Seattle, WA 98195 USA
{etzioni, dbgalur, soderlan, sammer} @cs.washington.edu
Abstract
We introduce a novel approach to the task of lexical translation. We utilize the translation graph, a massive
lexical resource where each node denotes a word in some language and each edge denotes a word sense shared
by a pair of words. Our current graph contains 1,267,460 nodes and 2,315,783 edges. The graph is automatically
constructed from machine-readable dictionaries and Wiktionaries. Paths through the graph suggest word transla-
tions absent from any of the input dictionaries. We define a probabilistic inference procedure that enables us to
quantify our confidence in a translation derived from the graph, and thus trade precision against recall.
We demonstrate the graph's utility by employing it in the PANIMAGES cross-lingual image search engine.
Google retrieves images based on the words in their "vicinity", which limits the ability of a searcher to retrieve
them. Although images are universal, an English searcher will fail to find images tagged in Chinese, and con-
versely. PANIMAGES addresses this problem by translating and disambiguating queries, using the translation
graph, before sending them to Google. Our experiments show that, for queries in "minor" languages, PANIM-
AGES increases the number of correct images in the first 15 pages of results by 75%.
1 Introduction

  

Source: Anderson, Richard - Department of Computer Science and Engineering, University of Washington at Seattle
Neumann, Günter - Deutsche Forschungszentrum für Künstliche Intelligenz

 

Collections: Computer Technologies and Information Sciences